Problem: In March 2020, the novel coronavirus 2019 (COVID-19) became a global pandemic. Medical schools around the United States faced difficult decisions, temporarily suspending hospital-based clerkship rotations for medical students due to potential shortages of personal protective equipment and a need to social distance. This decision created a need for innovative, virtual learning opportunities to support undergraduate medical education. Approach: Educators at Yale School of Medicine developed a novel medical student curriculum converting high-fidelity, mannequin-based simulation into a fully online virtual telesimulation format. By using a virtual videoconferencing platform to deliver remote telesimulation as an immersive educational experience for widely dispersed students, this novel technology retains the experiential strengths of simulation-based learning while complying with needs for social distancing during the pandemic. The curriculum comprises simulated clinical scenarios that include live patient actors; facilitator interactions; and real-time assessment of vital signs, labs, and imaging. Each 90-minute session includes 2 sets of simulation scenarios and faculty-led teledebriefs. A team of 3 students performs the first scenario, while an additional team of 3 students observes. Teams reverse roles for the second scenario. Outcomes: The 6-week virtual telesimulation elective enrolled the maximum 48 medical students and covered core clinical clerkship content areas. Communication patterns within the virtual telesimulation format required more deliberate turn-taking than normal conversation. Using the chat function within the videoconferencing platform allowed teams to complete simultaneous tasks. A nurse confederate provided cues not available in the virtual telesimulation format. Next Steps: Rapid dissemination of this program, including online webinars and live demonstration sessions with student volunteers, supports the development of similar programs at other universities. Evaluation and process improvement efforts include planned qualitative evaluation of this new format to further understand and refine the learning experience. Future work is needed to evaluate clinical skill development in this educational modality.

Introduction: Emergency medicine is characterized by high volume decision-making while under multiple stressors. With the arrival of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus in early 2020, physicians across the world were met with a surge of critically ill patients. Emergency physicians (EP) are prone to developing burnout and post-traumatic stress disorder (PTSD), due to experiencing emotional trauma as well as the cumulative stress of practice. Thus, calls have been made for attempts to prevent physician PTSD during this current pandemic. Methods: From July 2019–January 2020, emergency medicine (EM) resident physicians at a large, academic healthcare system were surveyed for symptoms of burnout using the Maslach Burnout Inventory (MBI). In late April and early May 2020, during the outbreak surge of coronavirus disease 2019 (COVID-19) in the Northeast USA, these same residents and the whole EM residency at the institution were again surveyed for symptoms of burnout as well as post-traumatic stress using the PTSD Checklist for Diagnostic and Statistical Manual of Mental Disorders, 5th Edition (PCL-5). A final survey was administered to the EM residents after the COVID-19 surge had largely subsided in June 2020. Results: Twenty-two residents participated in the pre-pandemic study and completed the MBI. Twelve (55%) completed the two follow-up MBI surveys. In the larger EM residency cohort, 31/60 residents completed the MBI and PCL-5 survey during the pandemic peak and 30/60 (50%) completed the follow-up surveys. There were no significant differences in the three MBI burnout category measures of emotional exhaustion (P = 0.49), depersonalization (P = 0.13), and personal accomplishment (P = 0.70) pre-, during, and post-COVID. Of 31 participants, 11 (35%) scored greater than 31 on the PCL-5. Two residents had scores between 21-30, interpreted as “at risk.” At greater than one month follow-up, 2/30 continued to meet criteria for a preliminary PTSD diagnosis, and five were “at risk.” Conclusion: A significant proportion of residents (35%) experienced post-traumatic symptoms acutely during the COVID-19 pandemic crisis, potentially indicating a high prevalence of acute stress disorder in this population and increased risk of developing PTSD. However, there was no significant difference in burnout levels in this cohort before, during, or after the initial COVID-19 surge. Early screening for physicians at risk and referral for assessment and treatment may be important to mitigate pandemic-related PTSD.

Journal of Medical Internet Research - International Scientific Journal for Medical Research, Information and Communication on the Internet #Preprint #PeerReviewMe: Warning: This is a unreviewed preprint. Readers are warned that the document has not been peer-reviewed by expert/patient reviewers or an academic editor, may contain misleading claims, and is likely to undergo changes before final publication, if accepted, or may have been rejected/withdrawn. Readers with interest and expertise are encouraged to sign up as peer-reviewer, if the paper is within an open peer-review period. Please cite this preprint only for review purposes or for grant applications and CVs (if you are the author). Background: Emergency Departments (EDs) frequently care for individuals with Opioid Use Disorder (OUD). Buprenorphine (BUP) is an effective treatment option for patients with OUD that can safely be initiated in the ED. At present, BUP is rarely initiated as a part of routine ED care. Clinical decision support (CDS) could accelerate adoption of ED-initiated BUP into routine emergency care. Objective: To design and formatively evaluate a user-centered decision support tool for ED initiation of buprenorphine for patients with OUD. Methods: User-centered design with iterative prototype development was used. Initial observations and interviews identified workflows and information needs. The design team and key stakeholders reviewed prototype designs to ensure accuracy. Five prototypes were evaluated and iteratively refined informed by feedback from 26 attending and resident physicians until thematic saturation was reached. Results: Early feedback identified concerns with the initial CDS design: an alert with several screens. The timing of the alert led to quick dismissal without using the tool. User feedback on subsequent iterations informed the development of a flexible tool to support clinicians with varied levels experience with the intervention by providing both one-click options for direct activation of care pathways as well as user-activated support for critical decision points. The final design resolved challenging navigation issues through targeted placement, color, and design of the decision support modules and care pathways. In final testing, users expressed that the tool could be easily learned without training and was reasonable for use during routine emergency care. Conclusions: A user-centered design process helped designers to better understand users’ needs for a web-based clinical decision tool to support ED initiation of buprenorphine for OUD. The process identified varying needs across user experience and familiarity with the protocol, leading to a flexible design supporting both direct care pathways and user-initiated decision support. Clinical Trial: N/A for design,

Background: The prevalence of adolescent mental health conditions such as depression and anxiety has significantly increased. Despite the potential of machine learning (ML), there is a shortage of models that use real-world data (RWD) to enhance early detection and intervention for these conditions. Objective: This study aimed to identify depression and anxiety in adolescents using ML techniques on RWD and social determinants of health (SDoH). Methods: We analyzed RWD of adolescents aged 10‐17 years, considering various factors such as demographics, prior diagnoses, prescribed medications, medical procedures, and laboratory measurements recorded before the onset of anxiety or depression. Clinical data were linked with SDoH at the block-level. Three separate models were developed to predict anxiety, depression, and both conditions. Our ML model of choice was Extreme Gradient Boosting (XGBoost) and we evaluated its performance using the nested cross-validation technique. To interpret the model predictions, we used the Shapley additive explanation method. Results: Our cohort included 52,054 adolescents, identifying 12,572 with anxiety, 7812 with depression, and 14,019 with either condition. The models achieved area under the curve values of 0.80 for anxiety, 0.81 for depression, and 0.78 for both combined. Excluding SDoH data had a minimal impact on model performance. Shapley additive explanation analysis identified gender, race, educational attainment, and various medical factors as key predictors of anxiety and depression. Conclusions: This study highlights the potential of ML in early identification of depression and anxiety in adolescents using RWD. By leveraging RWD, health care providers may more precisely identify at-risk adolescents and intervene earlier, potentially leading to improved mental health outcomes.

Objectives Agitation, defined as excessive psychomotor activity leading to aggressive or violent behaviour, is prevalent in the emergency department (ED) due to rising behavioural-related visits. Experts recommend use of verbal de-escalation and avoidance of physical restraint to manage agitation. However, bedside applications of these recommendations may be limited by system challenges in emergency care. This qualitative study aims to use a systems-based approach, which considers the larger context and system of healthcare delivery, to identify sociotechnical, structural, and process-related factors leading to agitation events and physical restraint use in the ED. Design Qualitative study using a grounded theory approach to triangulate interviews of patients who have been physically restrained with direct observations of agitation events. Setting Two EDs in the Northeast USA, one at a tertiary care academic centre and the other at a community-based teaching hospital. Participants We recruited 25 individuals who experienced physical restraint during an ED visit. In addition, we performed 95 observations of clinical encounters of agitation events on unique patients. Patients represented both behavioural (psychiatric, alcohol/drug use) and non-behavioural (medical, trauma) chief complaints. Results Three primary themes with implications for systems-based practice of agitation events in the ED emerged: (1) pathways within health and social systems; (2) interpersonal contexts as reflections of systemic stressors on behavioural emergency care and (3) systems-based and patient-oriented strategies and solutions. Conclusions Agitation events represented manifestations of patients’ structural barriers to care from socioeconomic inequities and high burden of emotional and physical trauma as well as staff members’ simultaneous exposure to external stressors from social and healthcare systems. Potential long-term solutions may include care approaches that recognise agitated patients’ exposure to psychological trauma, improved coordination within the mental health emergency care network, and optimisation of physical environment conditions and organisational culture.

Background: Electronic health record–based clinical decision support (CDS) tools can facilitate the adoption of evidence into practice. Yet, the impact of CDS beyond single-site implementation is often limited by dissemination and implementation barriers related to site- and user-specific variation in workflows and behaviors. The translation of evidence-based CDS from initial development to implementation in heterogeneous environments requires a framework that assures careful balancing of fidelity to core functional elements with adaptations to ensure compatibility with new contexts. Objective: This study aims to develop and apply a framework to guide tailoring and implementing CDS across diverse clinical settings. Methods: In preparation for a multisite trial implementing CDS for pediatric overweight or obesity in primary care, we developed the User-Centered Framework for Implementation of Technology (UFIT), a framework that integrates principles from user-centered design (UCD), human factors/ergonomics theories, and implementation science to guide both CDS adaptation and tailoring of related implementation strategies. Our transdisciplinary study team conducted semistructured interviews with pediatric primary care clinicians and a diverse group of stakeholders from 3 health systems in the northeastern, midwestern, and southeastern United States to inform and apply the framework for our formative evaluation. Results: We conducted 41 qualitative interviews with primary care clinicians (n=21) and other stakeholders (n=20). Our workflow analysis found 3 primary ways in which clinicians interact with the electronic health record during primary care well-child visits identifying opportunities for decision support. Additionally, we identified differences in practice patterns across contexts necessitating a multiprong design approach to support a variety of workflows, user needs, preferences, and implementation strategies. Conclusions: UFIT integrates theories and guidance from UCD, human factors/ergonomics, and implementation science to promote fit with local contexts for optimal outcomes. The components of UFIT were used to guide the development of Improving Pediatric Obesity Practice Using Prompts, an integrated package comprising CDS for obesity or overweight treatment with tailored implementation strategies. Trial Registration: ClinicalTrials.gov NCT05627011; https://clinicaltrials.gov/study/NCT05627011